The field of wireless communication networks has challenged implementers with continuously discovered synergies, both positive and negative. The sea of signaling has long grown from scattered and isolated sparks of Morse code to the modern-day roar of intermingling transmissions. The simplicity of the directional link (Point to Point) was replaced by the broadcast (Point to Multipoint) and is being replaced by the mesh (Multipoint to Multipoint) and even the relaying, multi-hop, interactive mesh; also, the continuous-transmission format is being replaced by short and varying packets. The complexities of variations in real world conditions—constantly changing topography, overlapping wave signals, and unpredictable and intermittent faults or blockages—all challenge the existing methods and systems. Further description of some of these problems are discussed as follows.
Wireless electromagnetic communication networks both enable competitive access to fixed link networks, whether they employ fiber, optical, or even copper lines, and provide a competitive alternative (such as linking computers in a WAN, or multiple appliances in an infrared network). The demand for high signal content capacity (above 1 to 2 MB/second) has increased dramatically in the last few years due to both telecommunications deregulation and the new service opportunities presented by the Internet.
Originally, wireless communication was either single-station to single-station (also known as point-to-point, PTP), or single-station to multiple station (also known as point-to-multiple-point, or PMP). PTP communication generally presumed equal capabilities at each end of the link; PMP communication usually presumed greater capabilities at the single core point than at any of the penumbral multiple points it communicated with. The topology of any PTP network was a disconnected set of linear links (FIG. 1); the topology of a PMP network was a ‘star’ or ‘hub and spoke’ (FIG. 2).
As the price for more complex hardware has declined and capability increased, PMP is winning over PTP. For economic reasons, a wireless electromagnetic communication network's nodes, or transceivers, usually vary in capacity. Most such wireless electromagnetic communication networks have a core hierarchy of Base Stations (BS), each comprising a multiplicity of sector antennae spatially separated in a known configuration, and a penumbral cloud of individual subscriber units (SU). If each BS communicates over a different frequency, then each SU must either have a tuned receiver for each station to which the subscriber tunes or, more commonly, a tunable receiver capable of reaching the range of frequencies encompassing those BSs to which it subscribes. (FIG. 3 shows two BSs and six SUs, four of whom subscribe to each BS, with different frequencies indicated in 3A and 3B.)
To increase the coverage in a given geographical area, PMP networks are typically deployed in multiple cells over the total service area of the network, with each SU linked to a single BS at a time except (in some mobile communication instantiations) during handoff intervals when it is transitioning from one cell to another. Although these cells are nominally non-overlapping, in reality emissions contained within one cell easily and typically propagate to adjacent cells, creating new problems of interference, as one cell's signal became noise to all other surrounding cells (intercell interference).
A number of different topologies (driven somewhat by the technology, and somewhat by the geography of the area in which the network existed), have been developed, including ring networks, both open and closed, and mesh networks. These efforts tried to maximize the coverage and clarity for the network as a whole, while minimizing the number of BS locations, minimizing BS complexity (and thus cost), and minimizing SU complexity (and thus cost).
The inherently multipoint nature of wireless communication networks, i.e., their ability to arbitrarily and flexibly connect multiple origination and destination nodes, has spawned a growing demand for methods and apparatus that will enable each particular wireless electromagnetic communication network to exploit their particular part of the spectrum and geography in constantly-changing and unpredictable economic and financial environments. Efficient use of both capacity and available power for a network, for a particular constraint set of frequencies, power, and hardware, is more in demand than ever as the competitive field and available spectrum grows more and more crowded.
The prior art includes many schemes for maximizing signal clarity and minimizing interference between nodes in a complex, multipoint environment. These include differentiation by: (a) Frequency channels; (b) time slots; (c) code spreading; and (d) spatial separation.
First generation systems (e.g. AMPS, NORDIC) developed for cellular mobile radio systems (CMRS) provide frequency-division multiple access (FDMA) communication between a BS and multiple SUs, by allowing each SU to communicate with the BS on only one of several non-overlapping frequency channels covering the spectrum available to the system. This approach allows each SU to ‘tune out’ those frequencies that are not assigned, or not authorized, to send to it. Intercell interference is then mitigated by further restricting frequency channels available to adjacent BS's in the network, such that BS's and SU's reusing the same frequency channel are geographically removed from each other; factor-of-7 reductions in available channels (“reuse factors”) are typically employed in first generation systems.
The total number of channels available at each BS is therefore a function of channel bandwidth employed by the system and/or economically usable at the SU. Hardware and regulatory limits on total spectrum available for such channels, and interference mitigation needs of the cellular network (cellular reuse factor), effectively constrain the divisibility of the spectrum and thus the geographical interacting complexity of current networks. (i.e. if the hardware requires a 200 kHz differentiation, and the network has 5 MHz of spectrum available, then 25 separate channels are available.) Channelization for most 1G cellular is 25-30 kHz (30 kHz in US, 25 kHz most other places; for 2G cellular is 30 kHz (FDMA-TDMA) for IS-136, 200 kHz for (FDMA-TDMA) GSM, 1.25 MHz for (FDMA-CDMA) IS-95; 2.5G maintains GSM time-frequency layout; and proposed and now-instantiated channelization for 3G cellular is FDMA-TDMA-CDMA with 5 MHz, 10 MHz, and 20 MHz frequency channels.
Most so-called second generation CMRS and Personal Communication Services (PCS) (e.g. GSM and IS-136), and ‘2.5 generation’ mobility systems (e.g., EDGE), further divide each frequency channel into time slots allocated over time frames, to provide Time Division Multiple Access (TDMA) between a BS and SUs. (For example, if the hardware requires at least 1 ms of signal and the polling cycle is 10 ms, only 10 separate channels are available; the first from 0 to 1 ms, the second from 1 to 2 ms, and so on.) The combination of TDMA with FDMA nominally multiplies the number of channels available at a given BS for a given increase in hardware complexity. This increase hardware need comes from the fact that such an approach will require the system to employ a more complex modulation format, one that can support individual and combined FDMA-TDMA, e.g., FM (for FDMA AMPS) versus slotted root-Nyquist .pi./4-DQPSK (for IS-136 and EDGE) or GMSK (for GSM).
Some second generation mobility systems (e.g. IS95), and most third generation mobility systems, provide code division multiple access (CDMA) between a BS and multiple SUs (for example, IS-136 provides FDMA at 1.25 MHz), using different, fixed spreading codes for each link. The additional “degrees of freedom” (redundant time or frequency transmission) used by this or other spread spectrum modulation can (among other advantages) mitigate or even exploit channel distortion due to propagation between nodes over multiple paths, e.g., a direct and reflection path (FIG. 4), by allowing the communicator to operate in the presence of multipath frequency “nulls” our outages that may be significantly larger then the bandwidth of the prespread baseband signal (but less than the bandwidth of the spread signal).
Different spreading code techniques include direct-sequence spread spectrum (DSSS) and frequency hop multiple access (FMHA); for each implemented, the hardware at each end of a link has to be able to manage the frequency and/or time modulation to encode and decode the signal correctly. Spreading codes can also be made adaptive, based on user, interference, and channel conditions. But each increase in the complexity of spread spectrum modulation and spreading code techniques useable by a network increases the complexity of the constituent parts of the network, for either every BS and SU can handle every technique implemented in the network, or the risk arises that a BS will not be able to communicate to a particular SU should they lack common coding
Finally, communication nodes may employ further spatial means to improve communications capability e.g. to allow BS's to link with larger numbers of SU's, e.g., using multiple antennae with azimuthally separated mainlobe gain responses, to communicate with SU's over multiple spatial sectors covering its service area. These antennae can provide space division multiple access (SDMA) between multiple SU's communicating with the BS over the same frequency channel, time slot, or spreading code, or to provide reuse enhancement by decreasing range between BS's allowed to use the same time slot or frequency channel (thereby reducing reuse factor required by the communication system). A BS may communicate with an intended SU using a fixed antenna aimed at a well-defined, fixed-angle sectors (e.g. Sector 1 being between 0 and 60 degrees, Sector 2 between 60 and 120 degrees, and so forth), or using an adaptive or “smart” antenna that combines multiple antennae feeds to optimize spatial response on each frequency channel and time slot. The latter approach can further limit or reduce interference received at BS or SU nodes, by directing selective ‘nulls’ in the direction of SU's during BS operations. (FIG. 5). This is straightforward at the BS receiver, more difficult at the BS transmitter (unless if the system is time-division duplex (TDD) or otherwise single-frequency (e.g., simplex, as commonly employed in private mobile radio systems)), or if the SU is based at “large” platforms such as planes, trains, or automobiles, or are used in other applications. This approach can provide additional benefits, by mitigating or even exploiting channel distortion due to propagation between nodes over multiple paths, e.g., a direct and reflection path. A further refinement that has been at least considered possible to adaptive SDMA signal management is the use of signal polarization, which can double degrees of freedom available to mitigate interference or multipath at BS or SU receivers, or to increase capacity available at individual links or nodes in the network. However, current implementations generally require antennae and transmissions with size or co-location requirements that are infeasible (measurable in meters) for high-mobility network units.
Various combinations of TDMA, CDMA, FDMA, and SDMA approaches have been envisioned or implemented for many other applications and services, including private mobile radio (PMR) services; location/monitoring services (LMS) and Telematics services; fixed wireless access (FWA) services; wireless local, municipal, and wide area networks (LAN's, MAN's, and WAN's), and wireless backhaul networks.
In other prior art implementations, a more-complex and capable BS assigns and manages the differentiation scheme or schemes among its SU's, using scheduling and assignment algorithms of varying power, complexity, and coordination to manage communications between the BS and its SU's, and between BS's in the overall wireless electromagnetic communications network. For all such networks, the key goal of these implementations are to provide a desired increase in capacity or performance (e.g., quality of service, power consumption, range, availability, or deployment advantage) in exchange for the increasing complexity and cost of the implementation. Everyone wants more bang for the buck, despite the limitations imposed by physics and hardware.
It is worth noting for the moment that none of the prior art contains means for managing power at the local level, that is, at each particular node, which benefits the wireless communications network as a whole. It is also worth noting that all encounter a real-world complexity: the more power that is poured into one particular signal, the more that signal becomes ‘noise’ to all other signals in the area it is sent to. (Even spatial differentiation only ‘localizes’ that problem to the given sector of the transmission; it does not resolve it.)
In two-way communication networks, the network must provide means to communicate in each link direction, i.e., from the BS to the SU, and from the SU back to the BS. Most PMP networks provide communication not only from the BS to the SU, and from the SU to the BS, but from one SU to a BS, thence to another BS, and eventually to another SU (FIG. 6A). This requires additional channels and fails to exploit possible diversity already present (FIG. 6B). Generally, each individual SU is less complex (in hardware and embedded software) than a BS to leverage the higher cost of the more complex BS over the many lesser SU nodes. Considerations affecting this provision in the prior art include: two-way communication protocols (so your signal is recognized as distinct from noise); traffic symmetry or asymmetry at the link or node, and user traffic models. Each of these is briefly discussed in turn.
Protocols are necessary to govern the transmission and reception process. Protocols that have been used to accomplish this in prior art include: (a) Simplex, (b) Frequency Division Duplex (FDD), and (c) Time Division Duplex (TDD) protocols.
A Simplex protocol, as the name suggests, enforces the simplest communication method: each communication is one-way, with the communication between two users occurring serially, rather than simultaneously. (E.g., the method still used by ham radio enthusiasts today, when a speaker signals the start of his message with his call sign or name, the end of one part of his message with ‘over’, and the end of his link to the recipient with, over and out′.) In this protocol, an originating node first transmits an entire message to a recipient node, after which the recipient node is provided with an opportunity to transmit back to the originating node. This retransmission can be a lengthy return message; a brief acknowledgement and possible request for retransmission of erroneous messages; or no message at all. Simplex protocols are commonly used in private mobile radio services; family radio networks; push-to-talk (PTT) radio links; and tactical military radios such as SINCGARS. Simplex protocols also form the basis of many ad hoc and random access radio systems such as Slotted ALOHA.
Two-way communication is much more complex (as anyone who has tried to speak and listen simultaneously can attest). Frequency Division Duplex (FDD) protocols divide the flow of communication between two widely separated frequency channels in FDMA networks, such that all “uplink” nodes (BS's) receive data from “downlink” nodes (SU's) over one block of uplink frequency channels, and transmit data back to the downlink nodes over a separate block of downlink frequency channels. The uplink and downlink blocks are separated at each end of the link using a “frequency diplexer” with sufficient isolation (out-of-block signal rejection) to allow the receive channel to be received without significant crosstalk from the (much stronger) transmit signal.
Time Division Duplex (TDD), though perceived by the users as being simultaneous, is technically serial; this protocol provides two-way communication in FDMA-TDMA networks by dividing each TDMA time frame into alternating uplink and downlink subframes in which data is passed to and from the uplink and downlink nodes (FIG. 8). The duration of the TDMA frame is short enough to be imperceptible to the network and user. It is both simpler to implement and uses less of the scarce bandwidth than FDD.
Traffic symmetry (and its reverse, asymmetry), refers to the relative uplink and downlink data rate, either on an individual link (uplink/downlink pair), or aggregated at an individual node in the network. For links, the question is whether the direction of the communication between one node and another makes a difference. If the uplink from the BS to the SU is substantively similar to the downlink from the SU to the BS, then the link communication is described as symmetric. On the other hand, if the downlink from the BS to the SU is substantially greater than any uplink from the SU to the BS, then the link communication is asymmetric. This can be envisioned as follows: does the communication link between node A and node B represent a pipe, or a funnel? It doesn't matter which way the pipe/funnel is pointing, it is the comparison between uplink and downlink capacity that determines the symmetry or asymmetry.
For nodes, the symmetry or asymmetry may refer to the relative capacity of one node to the others. When each BS has far more capacity than the individual SUs, the network's nodes are asymmetric (FIG. 9, where C and E>B and A>D). If, on the other hand, each node is reasonably alike in capacity, then they are symmetric. This is also known as a ‘peer-to-peer’ network. The former is the most common instantiation in the prior art for wireless electromagnetic communications networks.
A final consideration is the traffic model for the network as a whole. Just as a highway engineer has to consider more than the physics effecting each particular car at each point along the road when designing the interchanges and road system, those building a wireless multipoint electromagnetic communication network must consider how the communication traffic will be handled. The two dimensions, or differentiations, currently seen are (a) how individual communications are switched (i.e. how messages are passed along the links from the origination node to the recipient node and vice versa), and (b) how a particular communication is distributed amongst the set of nodes between the two end-points (i.e. whether a single path or diverse paths are used).
The two models for how communications are switched are the circuit-switched and packet-switched models. The former is best exemplified by the modern Public Switched Telephone Network (PSTN). When user A wants to communicate with user B, a definite and fixed circuit is established from A through any number of intervening points to user B, and that circuit is reserved for their use until the communication ends (A or B hangs up). Because the PSTN originated when all communication links had to be made by elements that shared the same capacity limit as the telephone users, that is, by human operators, they had no such excess capacity to exploit. (There was a point in time when economists extrapolated that the needed number of operators would exceed the number of human beings.) Fortunately automated circuit switching was developed.
The downside to the circuit-switched model is that the network's resources are used inefficiently; those parts comprising a given circuit are tied up during relatively long periods of dormancy, since the dedicated circuits are in place during active as well as inactive periods of conversations (roughly 40% in each link direction for voice telephony). This inefficiency is even more pronounced in data transmission systems, due to the inherent burstiness of data transport protocols such as TCP/IP.
The second model, ‘packet-switched’, is embodied in the much-more modern Internet. In this approach, the communication is divided up into multiple fragments, or packets, each of which is sent off through the most accessible route.
Whether the ‘circuit’ is a physical land-line, a frequency channel, or a time slot, does not matter; the import for the network is how the overall capacity is constrained when handling individual communications: on a link-by-link basis, or on a packet-by-packet basis.
The other differentiation, how a particular communication is distributed amongst the set of nodes between the two end-points, is between connection-oriented vs. connectionless communications. Connection-oriented communications establish an agreed-to, single, link path joining the two endpoints which is maintained throughout the communication; connectionless communications can employ multiple available link paths simultaneously. (The Internet's TCP/IP protocol is an exemplar of this approach.) Though there is a surface similarity between this differentiation and that of circuit/packet switching, the connection-oriented communication does not necessitate dedication of the entire capacity of each sub-part of the connection to the particular communication being handled; i.e. the network could ‘fill up’ an intermediate stage to that stage's capacity as long as it can split off the joined communications before the end is reached and avoid overloading any of the shared link sub-parts.
Again, it is worth noting for the moment that none of the prior approaches or differentiations provide means for power management for the network as a whole or present a potential solution to the real-world complexity whereby the more power that was poured into one particular signal, the more that signal became ‘noise’ to all other signals in the area it was sent to.
Presently, most wireless multipoint electromagnetic communication networks are PMP implementations. The disadvantages of these prior art wireless PMP wireless electromagnetic communication networks include:                (1) Requiring a predetermined distinction between hardware and software implemented in BS's and SU's, and in topology used to communicate between BS, as opposed to that used to communicate between a BS and its assigned SU's.        (2) Creating a need to locate BS's in high locations to minimize pathloss to its SU, and maximize line-of-sight (LOS) coverage, thereby increasing the cost of the BS with the elevation. (In urban areas, higher elevations are more costly; in suburban areas, higher elevations require a more noticeable structure and create ill-will amongst those closest to the BS; in rural areas, higher elevations generally are further from the service lines for power and maintenance personnel).        (3) Creating problems with compensating for partial coverage, fading and ‘shadowing’ due to buildings, foliage penetration, and other obstruction, particularly in areas subject to change (growth, urban renewal, or short and long range changes in pathloss characteristics) or high-mobility systems (FIG. 4).        (4) Balancing the cost of system-wide capacity increase effected by BS upgrades over subscribers who may not wish to pay for others' additional benefit.        (5) Creating problems with reduction in existing subscriber capacity, when new subscribers are added to a particular sector nearing maximal capacity (FIGS. 7A & 7B; if each BS can handle only 3 channels, then E and C can readily substitute in a new BS D, but neither A nor B can accept D's unused 3d channel).        (6) Balancing power cost in a noisy environment when competing uses of the spectra occur, either amongst the subscribers or from external forces (e.g. weather).        (7) Limiting capacity of the network to the maximum capacity of the BS managing the set of channels, and, (8) Losing network access for SU's if their BS fails.Multipoint Networks        
The tremendously increased efficiency of emplaced fiberoptic landlines, and the excess capacity of ‘dark fiber’ currently available, as well as the advent of new Low-Orbit Satellite (LOS) systems, pose a problem for any mobile, wireless, multipoint electromagnetic communication network. Furthermore, there is an ongoing ‘hardware war’ amongst the companies providing such networks. For with the increasing use of cellular wireless communications a ‘race up the frequencies’ has begun; no sooner does hardware come on the market enabling use of a new portion of the electromagnetic spectrum, than transmissions begin to crowd into it and fill both the geographic and frequency space. Both these dynamics acting together are further complicated by the potential merging of the single BS/multiple receiver (or ‘broadcast’) model of the radio fixed frequency range. Code division multiple access techniques, also referred to herein as CDMA, assign a signature to each subchannel which describes the pulse amplitude modulation, also referred to herein as PAM, to be used by the subchannel for communication. Well-known digital signal processing techniques may be applied to de-multiplex such multiplexed signals on the communication channel.
A variety of techniques have been applied to many of these known modulation methods to further improve the utilization of the channel bandwidth. It is a continuing problem to improve the bandwidth utilization of a channel so as to maximize the data throughput over the channel. In particular, it is a continuing problem to dynamically adapt the multiplexing techniques to maximize network performance over particular signaling patterns, usage, and power. As mobile transmitters and receivers are moved relative to one another, channel bandwidth utilization efficiency may change. It is a problem to adapt presently known multiplexing techniques to such dynamic environmental factors.
Problems identified in M. K. Varanasi's U.S. Pat. No. 6,219,341 include designing signature waveforms for a particular channel, multiplexing a plurality of digital data streams over a communications channel, and making a communications channel dynamically adaptable. That patent focuses on non-multipath environments where a single available channel with a fixed frequency range and multiple receiving devices exist; there are not a multiplicity of antennae at either receiver(s) or at the transmitter, and no network-effect adaptations and methodologies. That patent provides many references to work on the problem of multiple access communications problem is one where several autonomously operating users transmit information over a common communications channel, which do nor resolve problems such as:                “Multiple-Access (FDMA) techniques pre-assign time or frequency bands to all users . . . absurdly wasteful in time and bandwidth when used in applications where communications is bursty as in personal, mobile, and indoor communications. In such applications, some form of dynamic channel sharing is therefore necessary . . . ”; and, and television fields with the linked pair-sets (two inter-communicating nodes) or ‘dedicated channel’ model of the plain old telephone system (PSTN).        
The race is becoming even more frenetic as voice and data communications merge. This evolution must accommodate packet-switched, connectionless data protocols such as TCP/IP, which transmits data in multiple bursts over multiple communication channels. The topologies and capacities, of these channels may change during a communication session, requiring complex and burdensome routing and resource management to control and optimize the network Finally, future wireless electromagnetic communications networks may need to communicate with mobile platforms (e.g., automobiles in Telematics applications), peripherals (e.g., printers, PDAs, keyboards), and untethered ‘smart’ appliances, further increasing connectivity capacity, and quality of service (QoS) needs of the network. Nowadays, advanced wireless electromagnetic communications networks must routinely handle both voice and data communications, and communications amongst people, between people and devices, and between devices.
Prior art knows to use radio frequency communication channels to transfer digital data between devices, and to encode digital data on a channel such that a parameter of the communication channel is modulated in accordance with the values of the digital data bit sequence to be transferred. Many applications of such communication channels permit multiple, simultaneous access to the channel by a plurality of digital data streams, for example, a plurality of digitized voice data streams or a plurality of computer digital data streams. The plurality of digital data streams is multiplexed over the communication channel by subdividing the channel into a plurality of subchannels each characterized by unique communication parameters which may be de-multiplexed at the opposite end of the communication channel.
The communication techniques referred to above (CDMA, TDMA, FDMA), are also known to be useful for such subdivision of a communication channel. For example, time division multiple access, also referred to herein as TDMA, multiplexes the subchannels onto the channel by assigning each subchannel a period of time during which the subchannel uses the channel exclusively. Frequency division multiple access techniques, also referred to herein as FDMA, assign each subchannel a sub-range of the                “While Random Multiple Access techniques such as ALOHA allow dynamic channel sharing [citation omitted] . . . they are, however, unsuitable for the aforementioned applications where there is usually more than one active transmitter at any given time.”        
Other techniques identified in Varanesi are Dynamic TDMA (which requires both a reservation and a feedback channel, cutting the channels available for content and increasing the network system overhead), adaptive timing enforcement rather than user-signal differentiation; differentiation between BS and SU signal management; use of linear PAM pre-assigned rather than dynamic adaptation; presuming transmissions are limited to the number of active simultaneous transmitters instead of allowing differentiated symbol (e.g. QAM) division of any particular channel into subchannels; assigning, statically, a signature waveform to every transmitter and not adapting to network flows. Reservation channels are also used in dynamic CDMA, which are also limited to pre-designed waveforms and BS units only. In the prior art, Varanesi in particular asserts:                “ . . . when a carrier is not lightly loaded, so that the number of active users for that carrier is a sizeable fraction of the assigned spread factor, decorrelative and linear MMSE detectors . . . [citations omitted] . . . will not be satisfactory . . . ”and,        “ . . . the hardware costs of base-stations in FDMA are higher in that they must have as many transceivers as the maximum number of users allocated per carrier (see R. Steele supra) whereas dynamic SSMA only requires one transceiver per carrier.”        
Varanesi's BEMA approach suffers from a several significant defects in modern, high-mobility, rapidly-changing communication network environments: (1) “the signature waveforms are specifically designed for that receiver”, and, (2) “they may be slowly re-allocated as the traffic conditions—such as the received power levels and number of active transmitters—change and evolve”. In the dynamic, mobile, constantly-changing environment these constraints do not allow enough adaptivity and flexibility. As the number of common users grows, the risk develops of an electromagnetic repetition of Garrett Hardin's ‘tragedy of the commons’; in short, that mutual signaling devolves to shared noise. Simply adding power, or additional frequencies, works only as a short-sighted or short term solution; the real need is for networks that make use of multipath and multiple user effects rather than ignore them. (FIGS. 10 and 11 respectively exemplify static and mobile multipath environments.)
Various approaches to treating other users of the communications channel (or frequency) briefly mentioned in Varanesi also include: “(a) treat mutual inter-user interference as additive noise; (b) treat uncancelled inter-user interference as additive noise; and, (c) decorrelate uncancelled interference.” But the concept of using the signaling from multiple sources as a way of harmonizing and organizing the information, and identifying the channel diversity and environmental conditions to allow adaptation and optimization, is nowhere there suggested.
Beamforming is a particular concern for wireless electromagnetic communications networks, especially where a network is dense or where there are portable, low-mobility, or high-mobility SU. Within wireless mobile communication systems, four techniques have been developed for improving communication link performance using directive transmit antennas: (i) selection of a particular fixed beam from an available set of fixed beams, (ii) adaptive beam forming based on receive signal angle estimates, (iii) adaptive transmission based on feedback provided by the remote mobile SU, and (iv) adaptive transmit beam forming based upon the instantaneous receive beam pattern. Each of these prior art techniques is described briefly below.
In the first technique, one of several fixed BS antenna beam patterns is selected to provide a fixed beam steered in a particular direction. The fixed antenna beams are often of equal beam width, and are often uniformly offset in boresight angle so as to encompass all desired transmission angles. The antenna beam selected for transmission typically corresponds to the beam pattern through which the largest signal is received. The fixed beam approach offers the advantage of simple implementation, but provides no mechanism for reducing the signal interference power radiated to remote mobile SU(s) within the transmission beam of the BS. This arises because of the inability of the traditional fixed beam approach to sense the interference power delivered to undesired users.
The second approach involves “adapting” the beam pattern produced by a BS phase array in response to changing multipath conditions. In such beamforming antenna arrays, or “beamformers”, the antenna beam pattern is generated so as to maximize signal energy transmitted to (“transmit beamforming”), and received from (“receive beamforming”), an intended recipient mobile SU.
While the process of transmit beamforming to a fixed location over a line-of-sight radio channel may be performed with relative ease, the task of transmitting to a mobile SU over a time-varying multipath communication channel is typically considerably more difficult. One adaptive transmit beamforming approach contemplates determining each angle of departure (AOD) at which energy is to be transmitted from the BS antenna array to a given remote mobile SU. Each AOD corresponds to one of the signal paths of the multipath channel, and is determined by estimating each angle of arrival (AOA) at the BS of signal energy from the given SU. A transmit beam pattern is then adaptively formed so as to maximize the radiation projected along each desired AOD (i.e., the AOD spectrum), while minimizing the radiation projected at all other angles. Several well known algorithms (e.g., MUSIC, ESPRIT, and WSF) may be used to estimate an AOA spectrum corresponding to a desired AOD spectrum.
Unfortunately, obtaining accurate estimates of the AOA spectrum for communications channels comprised of numerous multipath constituents has proven problematic. Resolving the AOA spectrum for multiple co-channel mobile SUs is further complicated if the average signal energy received at the BS from any of the mobile SUs is significantly less than the energy received from other mobile SUs. This is due to the fact that the components of the BS array response vector contributed by the lower-energy incident signals are comparatively small, thus making it difficult to ascertain the AOA spectrum corresponding to those mobile SUs. Moreover, near field obstructions proximate BS antenna arrays tend to corrupt the array calibration process, thereby decreasing the accuracy of the estimated AOA spectrum.
In the third technique mentioned above, feedback information is received at the BS from both the desired mobile SU, and from mobile SUs to which it is desired to minimize transmission power. This feedback permits the BS to “learn” the “optimum” transmit beam pattern, i.e., the beam pattern which maximizes transmission to the desired mobile SU and minimizes transmission to all other SUs. One disadvantage of the feedback approach in the prior art is the presumption that the mobile radio needs to be significantly more complex than would otherwise be required. Moreover, the information carrying capacity of each radio channel is reduced as a consequence of the bandwidth allocated for transmission of antenna training signals and mobile SU feedback information. The resultant capacity reduction may be significant when the remote mobile SU move at a high average velocity, as is the case in most cellular telephone systems.
The fourth conventional technique for improving communication link performance involves use of an optimum receive beam pattern as the preferred transmission beam pattern. After calibrating for differences between the antenna array and electronics used in the transmitter and receiver, it is assumed that the instantaneous estimate of the nature of the receive channel is equivalent to that of the transmit channel. Unfortunately, multipath propagation and other transient channel phenomenon have been considered to be problems, with the prior art considering that such substantially eliminate any significant equivalence between frequency-duplexed transmit and receive channels, or between time-division duplexed transmit and receive channels separated by a significant time interval. As a consequence, communication link performance fails to be improved.
At any given point the hardware, bandwidth, and user-determined constraints (Quality of Service, number of users simultaneously communicating, content density of communications) may demand the utmost from the system. Not only must a modern wireless electromagnetic communications network simultaneously provide the maximum capacity (measured by the number of bits that can be reliably transmitted both over the entire network and between any given pair of sending and receiving nodes in that network), but also, it must use the least amount of power (likewise measured over the entire network and at each particular node). Because, in any increasingly crowded electromagnetic spectrum, capacity and power are interactive constraints. To optimize the system over the sweep of potential circumstances, with minimal duplication or resource expenditure, designers must attain the greatest capacity and flexibility for any given set of hardware and signal space. In a wireless electromagnetic communication network, and more particularly in a cellular communication network, the greatest capacity and flexibility are offered by multipoint, or multiple-input and multiple-output (MIMO) systems.
Prior implementations of MIMO systems have been limited to point-to-point links exploiting propagation of signal energy over multiple communication paths, for example, a direct path and one or more reflection paths. In this environment, link capacity can be increased by employing an array of spatially separated antennas at each end of the link, and using these arrays to establish substantively orthogonal links that principally exploit each of these communication paths. Mathematically, the channel response between the multiple antennas employed at each end of the link has a multiple-input, multiple-output (MIMO) matrix representation, hence the term “MIMO link” for this case. (See FIG. 12, which exemplifies just such a physical PTP multipath, consisting of one direct and two reflective links, as shown graphically in FIG. 10; then contrast that to the data flow diagram of such a PTP link in FIG. 11.)
Using the tools of information theory disclosed in the referenced patent applications, Paulraj and Raleigh have shown that these links can approach the maximum capacity of the point-to-point communication channel (given appropriate power constraints and spatially and temporally “white” additive Gaussian background noise) by (1) dividing the channel into “substantively orthogonal frequency subchannels,” or time-frequency subchannels, and then, on each subchannel (2) redundantly transmitting multiple data “modes” (spatial subchannels within each time-frequency subchannel) over multiple antennas using vector linear distribution weights that are proportional to the “right-hand” eigenvectors of the MIMO channel frequency response on that subchannel, and, next, (3) combining receive antenna array elements using vector linear combiner weights that are proportional to the “left-hand eigenvectors of the MIMO channel frequency response on that subchannel, to recover the data mode transmitted using the corresponding right-handed eigenvector of the MIMO channel response on that subchannel. The vector transmit weights are then (4) further scaled to provide a normalized response dictated by a “water filling” formula computed over the aggregate set of subchannels and data modes employed by the communication link, based on the eigenvalues of the MIMO channel frequency response on each subchannel, and a vector coding formula (sometimes referred to as a “space-time” or “space-frequency” code) is used to (5) transmit data over each subchannel and data mode at the maximum bits/symbol (or transmit efficiency) (or data rate) allowed by the received signal-to-noise ratio on that subchannel and data mode.
Raleigh has also shown that this capacity of a MIMO PTP link increases nearly linearly with the number of antennas employed at each end of the link, if the number of propagation paths is greater than or equal to the number of antennas at each end of the link, the pathloss over each path is nearly equal, and either (1) the spatial separation between paths is large in some sense (e.g., the propagation occurs over paths that impinge on the link transceivers at angles of transmission and reception that are greater than 1/10 the “beamwidth of the array), (2) the antenna elements are separated widely enough to provide statistically independent channel response on each MIMO path (e.g., if the antennas are separated by greater than 10 times the wavelength of the transmission frequency in Raleigh fading channels).
Raleigh has also shown that a PTP MIMO channel response (allowing implementation of high capacity links exploiting this channel response) can also be induced by redundantly transmitting data over polarization diverse antennas using the procedure described above. In U.S. Pat. No. 6,128,276, Agee has also shown that a PTP MIMO channel response can be induced by redundantly transmitting data over multiple frequency channels or subchannels. In fact, MIMO channel responses can be induced by redundantly transmitting data over combinations of “diversity” paths, including independent spatial paths, independent polarization paths, independent, frequency channels, or independent time channels.
Paulraj, Raleigh, and Agee teach many additional advantages for MIMO PTP links, including improved range through exploitation of “array gain” provided by transmit and receive antennas; non-line-of-sight communication over reflections from buildings and ducting down streets; and reduced transmit power through ability to achieve desired capacities at lower power levels at each antenna in the arrays. Agee also teaches means for adjusting the array adaptively and blindly, based on receive exploitation of signal coding added during transmit operations; for nulling interference signals at each transceiver; and for exploiting reciprocity of the MIMO channel response to adapt transmit weights in TDD PTP links.
Agee, B. G. et. al. added some indication in the patent application Ser. No. 08/804,619, filed on Feb. 24, 1997, titled “Highly Bandwidth-Efficient Communications”, since abandoned but pursued in part in Ser. No. 08/993,721 (now U.S. Pat. No. 6,359,923), to discrete spread-spectrum, non-orthogonal multitone approaches, and indicated that MIMO systems may have additional benefits in point-to-multipoint and cellular PMP networks.
In a MIMO system, the nodes at each end of a link will have multiple antennae, and establish between them one link per pair of antennae. (There can still be a BS/SU division; for example, a BS may have 20 pairs of antennae, while each SU have but 2 pair, or 4, antennae, thereby allowing a 1-10 BS/SU ratio without any overlap.) In “Wireless Personal Communications: Trends and Challenges”, pp. 69-80, Rappaport, Woerner, and Reeds, Editors, Kluwer Academic Publishers, 1994, at p. 69 Agee notes: “the use of an M-element multiport antenna array at the BS of any communication network can increase the frequency reuse of the network by a factor of M and greatly broaden the range of input SINRs required for adequate demodulation . . . ”.
Some of the mathematical background for MIMO generally can be found in E. Weinstein et. al.'s U.S. Pat. No. 5,539,832 for “Multi-channel signal separation using cross-polyspectra”, which speaks specifically to a limited field of separating signals from received from plural sources. That considered linear time invariant (LTI) MIMO systems, noting that sample response matrices and frequency vectors, vector-valued time and frequency indices could be used.
In cellular wireless systems, a BS transceiver simultaneously communicates with several mobile users. In such systems, an antenna array at the central base can improve the quality of communication with the mobile users and increase the number of users supportable by the system, without the allocation of additional bandwidth. But a problem may arise when a SU can communicate with multiple BSs and cause unexpected diversity and interference. (This is one of the principal reasons cell phone use from airlines is restricted; the in-air SU is effectively equidistant to many BSs and that network suffers.)
To increase quality of the communication in a wireless system, an antenna array can provide diversity to combat fading. Fading of the base-mobile link is due to destructive interference of the various multipaths in the propagation medium, and at times can cause signal attenuation by as much as 30 dB. Time and frequency diversity are traditional techniques which are highly effective in preventing signal loss. An antenna array can be used to provide beampattern diversity, which is an additional technique that supplements time and frequency diversity.
To increase capacity in a wireless system, an antenna array can implement same cell frequency reuse, which recognizes that each signal typically has a different angle of arrival at the BS. Using this technique, the base sends signals to multiple receivers on the same time/frequency channel within the same sector, and uses a separate beam to minimize crosstalk and maximize desired signal for each receiver. Such beams provide a means of reusing the resources of time and bandwidth, and they overlay with the traditional means of multiplexing such as (T/F/CDMA). Same cell frequency reuse is also sometimes known as spatial division multiple access (SDMA).
There are two aspects to using antenna arrays at the base in mobile radio: receive antenna processing (reverse link) and transmit antenna processing (forward link). In the forward link approach, there are “open loop” and “closed loop” approaches. An “open loop” approach is explored by G. Raleigh et al. in “A Blind Adaptive Transmit Antenna Algorithm for Wireless Communication,” International Communications Conference, 1995. This transmit beamforming method uses the reverse link information signals sent by the mobiles as a means of determining the transmit beampatterns. This “open loop” method, however, does not provide the transmitter with feedback information about the transmitted signals, and is consequently less robust to changes in the propagation medium than feedback methods.
In contrast to the “open loop” approach, the “closed loop” approach uses an additional feedback signal from the mobiles. The transmitting array has no a priori knowledge of the location of the mobiles or the scattering bodies, and an adaptive antenna array can use a feedback signal from the mobile receivers to give the transmitter a means of gauging its beampatterns. Because of multipath, an array that simply directs a mainlobe towards a mobile may result in a fade of the desired signal or crosstalk to other mobiles. So unless the base can also account for all of the scattering bodies in the environment, undesired crosstalk or fading is liable to occur. Since adaptive transmitting antennas do not possess built-in feedback, the receivers must provide a feedback signal to enable the transmitter to function effectively in this approach.
In U.S. Pat. No. 5,471,647, “Method for Minimizing Cross-Talk in Adaptive Transmission Antennas,” which is hereby incorporated by reference, Gerlach et al. present a method of multiple signal transmission using an antenna array and probing signals together with feedback from the receivers back to the transmitter. This probing-feedback method allows the transmitter to estimate the instantaneous channel vector, from which the transmitting beamformer ensures signal separation even in the face of time-varying multipath in the propagation medium. This method is further described by Gerlach et al. in the following articles which are hereby incorporated by reference: “Spectrum Reuse Using Transmitting Antenna Arrays with Feedback,” Proc. International Conference on Acoustics, Speech, and Signal Processing, pp. 97-100, April 1994; “Adaptive Transmitting Antenna Arrays with Feedback,” IEEE Signal Processing Letters, vol. 1, pp. 150-2, October 1994; and “Adaptive Transmitting Antenna Arrays with Feedback,” IEEE Transactions on Vehicular Technology, submitted October 1994.
While the method of D. Gerlach et al. In U.S. Pat. No. 5,471,647 purportedly minimizes crosstalk and eliminates fading, Gerlach identifies, in a later patent, a major problem therein: it is limited by the high feedback data rates that are required to track the instantaneous channel vector. High feedback data rates are undesirable because they require a large channel capacity on a link from the receivers back to the transmitter.
If the transmitter is located in an urban environment or other cluttered area, scattering from buildings and other bodies in the propagation medium creates an interference pattern. This interference pattern contains points of constructive and destructive interference, spaced as little as one-half wavelength apart. As the receiver moves through such an environment, the channel vector can change significantly when the receiver moves as little as one-tenth of a wavelength. Consequently, the transmitter must repeatedly estimate a new channel vector by sending probing signals and receiving feedback. The feedback rate needed is 19,200 bps for a receiver moving 30 mph receiving a 900 MHz carrier using a six element array with four bit accuracy. Gerlach concluded that (1) the need for such high feedback rates renders antenna arrays impractical for most applications; and (2) in addition to high feedback rates, the method of D. Gerlach et al. can be difficult to implement because the air interface standard would have to be changed to add in the feedback feature. The users would have to exchange their old handsets for new ones that are compatible with the new feedback standard. This is a costly and impractical modification.
Several alternative approaches to the limited problem of minimizing crosstalk in a wireless communications system were disclosed in D. Gerlach, et. al.'s later U.S. Pat. No. 5,634,199. These included the use of information weight vectors that minimized the time-average crosstalk, matrices (subcorrelation and autocorrelation), linear combination of diversity vectors, and dominant generalized eigenvectors. Furthermore, their approach presumed that multiple antennae only existed at the system's BS, rather than at each node. However, the methods disclosed therein still require significant network capacity be devoted to cross-system signal management rather than signal content.
Another approach is to design the network such that at every point multipath can be actively avoided and direct line of sight exists between each SU and a member of a subset of nodes, said subset members also having a line of sight amongst themselves in a mesh, as in Berger, J. et. al., PCT WO 00/25485, “Broadband Wireless Mesh Topology Network”. That patent notes that its applicability is limited to the frequencies above 6 GHz, and specifically below 3 GHz, “ . . . where multiple reflections via non line of sight reception interfere dramatically with the network performance and reduce the network capacity when subscriber count increases in the area.”
However, the approaches suggested in the prior art, (Paulraj, Raleigh, Agee, et. al.) are not generally feasible or economical in many applications. For example, the 10-wavelength rule-of-thumb for statistically independent MIMO propagation path can be difficult to achieve in mobility applications, which typically require transmission of signal energy at well below 10 GHz (3 cm, or 1/10 foot, wavelength) to avoid dynamic, stability, and weather affects prevailing above that frequency. A 10-wavelength antenna separation corresponds to 1-to-10 feet at frequencies of 1-to-10 GHz, achievable at BSs in mobility systems (for small numbers of antennas), but not practical in mobile SU's. However advantageous the improvements might be from going to a MIMO system (e.g. reducing fading and co-channel interference), the human factor (namely, that people would not walk around with meter-plus wide antennae) militated against adoption of this approach. Even the tremendous capacity improvement of 400% suggested by Paulraj for a MIMO approach would not overcome this consideration. Additionally, much of the prior art presumes that any MIMO network necessarily must reduce the Signal-to-(Interference and) Noise Ratio (SINR) in the multipath channel to zero.
In U.S. Pat. No. 6,067,290, Spatial Multiplexing In A Cellular Network”, A. J. Paulraj et. al. claim methods and apparatus for the purpose stated in that title, noting that:                “Since there are quite a few services (e.g. television, FM radio, private and public mobile communications, etc.) competing for a finite amount of available spectrum, the amount of spectrum which can be allocated to each channel is severely limited. Innovative means for using the available spectrum more efficiently are of great value. In current state of the art systems, such as cellular telephone or broadcast television, a suitably modulated signal is transmitted from a single base station centrally located in the service area or cell and propagated to receiving stations in the service area surrounding the transmitter. The information transmission rate achievable by such broadcast transmission is constrained by the allocated bandwidth. Due to attenuations suffered by signals in wireless propagation, the same frequency channel can be re-used in a different geographical service area or cell. Allowable interference levels determine the minimum separation between base stations using the same channels. What is needed is a way to improve data transfer speed in the multiple access environments currently utilized for wireless communications within the constraints of available bandwidth.”        
Paulraj et. al. also presumes a division between BS and SU, where the BS performs all of the adaptation, which either requires information or control signals from each of the SUs that adds significantly to the signaling overhead, or limits the adaptive process to that observable and attainable solely by the BS in response to control signals from the SUs. Paulraj also identifies the minimum spatial separation between antennae as ½ the carrier wavelength, i.e. ½.lamda. Furthermore, Paulraj lacks the concepts of adaptive reciprocity, network MIMO management, LEGO, power management, power optimization, capacity optimization or capacity management. Though Paulraj speaks to using multipath, there is at best limited implementation in situations where multipath is stable and guaranteed, rather than true opportunistic implementation in a dynamic and adaptive fashion.
In U.S. Pat. No. 6,006,110, G. G. Raleigh describes a time-varying vector channel equalization approach for adaptive spatial equalization. That patent's concern is with compensating for multipath effects, rather than exploiting them.
In his later U.S. Pat. No. 6,101,399, G. G. Raleigh et. al. made the concept of his 1995 paper, referenced above, the basis for that patent for “Adaptive Beam Forming, for transmitter operation in a wireless communication system”. In that paper, all of the adaptation takes place at the BS (which has an adaptive antenna array), and none at the substantially different SU (which in the preferred embodiment does not). This patent uses no feedback from the receiver to the transmitter, with transmitter weights being variously generated through an estimated desired receive channel covariance matrix and an undesired interference covariance matrix, or from a pre-designed or predetermined transmit beam pattern weight vectors. It also has no local modeling, no network management aspects, and makes no effort to exploit opportunistic multipath; and its chief solution to a deteriorating signal capacity is to simply shift the most heavily impacted user away to a different frequency (which presumes one is available). Paulraj and Raleigh do not consider means for extending MIMO PTP links to applications containing multiple simultaneous links, e.g., multipoint networks (such as the PMP and cellular PMP mobility network described above). In addition, these approaches do not either adequately treat means for controlling such a network, or address several key conundra limiting MIMO application.
Diversity: The Interference Conundrum
Even assuming that a MIMO approach is desirable, or that the antenna size problem mentioned above could be ignored, the prior art faced a contradiction that argued against MIMO efforts. First, to any particular wireless link, signals generated on all other links are interference. Second, closely coincident signals can heterodyne to produce a resultant signal that is different than any of its constituent elements. Because MIMO increases the number of coincident signals, it was seen as increasing the resultant noise against which the information-carrying signal had to be detected. Multiple access and interference are seen by many as the single largest problem and system limitation.
Capacity as One Key Network Metric
The explosive demand for delivery of integrated voice and data communications over the ‘last mile’ amongst all possible nodes (humans, peripherals, appliances, desktops, or servers) has spurred increased research into means for providing such communications in wireless electromagnetic networks. Wireless, because the cost of either initially installing, or subsequently dynamically altering, the network more often represents irretrievably sunk capital in equipment which cannot keep up with the design-build-install product cycles. Wireless, because users are increasingly demanding that their communication provisioning be untethered from predetermined geographic point locations, to meet the mobility demands placed upon them. In all of these demands, a key metric affecting cost and quality of any wireless electromagnetic communications network is the capacity of the network for any given set of internode channel responses, receive interference levels, channel bandwidths, and allowable or attainable transmission powers.
Capacity is a problem that has been studied extensively for PTP approaches, where the well-known ‘water filling’ solution for the maximum capacity communication over channels with frequency selective noise and/or channel distortion. However, Paulraj and Raleigh do not consider means for extending MIMO PTP links to applications containing multiple simultaneous links, e.g., multipoint networks (such as the PMP and cellular PMP mobility network described above). In addition, these approaches do not adequately treat means for controlling such a network. In “Highly Bandwidth-Efficient Communications”, U.S. patent application Ser. No. 08/804,619, abandoned and replaced by its continuation, Ser. No. 08/993,721, Agee, et. al., discloses a solution for extending MIMO diversity exploitation to PMP and cellular PMP networks and for controlling such a network using local operations at individual nodes, by exploiting channel reciprocity to optimize network-wide mean-squared error (MSE) of time-division duplex (TDD) multi-cell PMP networks. That application discloses a solution that is severely limited. The solution optimizes an “ad hoc” metric (sum of mean-square error at each node in the network) that does not directly address any true measure of network quality, hence it can be substantively suboptimum with respect to such a metric. For example, the solution cannot simultaneously control transmit power and combiner output signal-to-interference-and-noise ratio (SINR) at both end of the link, and generally provides a solution that controls power subject to a global SINR constraint that may be hugely overachieved (to detriment of overall network performance) at some nodes in the network. The solution does not address networks with significant non-network interference, if that interference is nonreciprocal, for example, if that interference is only observable at some nodes in the network, or non-TDD protocols in which internode channel responses may be reciprocal, e.g., single-frequency simplex networks. Most importantly, however, that solution only addresses cellular PMP networks, not general MIMO networks.
Capacity as a metric is complicated by one further factor: the network must use its own capacity to communicate about its messaging and traffics, which puts a complex constraint on the network. The more that it tries to communicate about how to manage itself well, the less capacity it has to carry other messages from the users, as opposed to the administrators, of the network.
Overhead vs. Content Conundrum
Ongoing capacity control for a wireless electromagnetic communications network is the control of network overhead as much as the control of the network content. The more complex the environment and the system, the greater the following conundrum: detailed network control (which necessarily includes signals containing information about the network and the entire environment, separate from the signals containing the content being sent through the network operating in that same environment) steals capacity from the network. The more the message space becomes filled with messages managing that same space, the less room there is for messages using that space to convey content amongst the nodes. The increase in such top-level network overhead grows at a more-than-geometric rate with the growth of any network, for not only must the information about the network keep pace with its geometric growth, but also the information must come on top of the messages which actively manage the network. Feedback on top of control on top of signals, when grown globally, rapidly eat up advances in hardware or software.
Automation, or turning signal processing into hardware, cannot by itself resolve this conundrum. While hardware advances can rapidly overcome human limitations, they can never overcome their inherent limitations, process more signals, or process the extant signals more complexly, than the hardware is designed to do. Every element in the network, from the CODECs to the MUXs to the wireless transceivers, can only work at less than their optimum capacity. The approach that of necessity approaches, asymptotically, the optimal capacity for message content in a wireless electromagnetic communications network is that which manages the communications with the least overall network burden. For any given hardware and software of a network, that which manages best does so by managing least—at least as far as burdening the capacity is concerned.
In network management the content dynamics change over time, in such a fashion that there are always individual nodes that are operating at less than capacity and thus have potential capacity to spare. (If only because some node is processing a control command, which lessens the content it is sending out, which decreases the load on its neighbors, which then are free to change their control, and so forth.) Overhead control which depends on centralization can never take full advantage of such momentary and dynamic opportunities, because of the simple fact that the message informing the central controller of the opportunity itself reduces the overall capacity by the amount needed to transmit such a message (and to handle all the consequential operations ordered by the controller). Capacity control therefore becomes both a local and a global concern; the network must neither overload any particular node (requiring the repetition of lost or dropped messages, and thereby decreasing the total capacity since the sender's original signal becomes wasted), nor overload the entire system (with, for example, measurements of remaining global capacity, taking away signal space that otherwise could have been used for node-directed content.
One of the limitations of the prior art is that most systems block out a part of the network capacity as a network signaling preserve, which operates to communicate between the transmitters and receivers information concerning the external environment, such as the amount of external interference along any particular link or channel, and the perceived Signal to (Interference and) Noise Ratio (SINR) for a transmission. The more complex, or the more crowded, the network becomes the greater this drain of overhead on available capacity for a given infrastructure. Because the environment, the network, or (most frequently) both will change over time, network designers tend to allocate greater-than-necessary amounts to account for unforeseen future complications. These signal subspaces within the network, when they are used to measure the signal, path, multipath, or interference, are only actively needed part of the time, yet the loss of capacity continues all of the time. If, on the other hand, they are temporally divided, then they must come into existence and use when the network is at its busiest to best tune the system—and thereby impose additional overhead and reduce capacity precisely when it is most valuable to the network.
Another limitation of the prior art is the presumption that the signal space is uniformly shaped over time, wherein network averages or constraints, rather than network usage, guides the signaling process. This requires overdesign and overprovisioning to ensure a guaranteed minimal state regardless of both internal and external environmental factors.
Existing Capacity Management
Among the means used by the prior art to manage capacity are: (1) the use of signal compression and decompression to manage signal density, permitting point-to-point capacity maximization over a given set of links by handling multiple-access channels wherein signals sent at one higher, denser, frequency can be divided into a set of subordinate signals sent at a set of lower frequencies, i.e. where a 10 MHz signal becomes ten 1 MHz signals; (2) using multipath, multiple-antenna links between given pairs of nodes with prior channel capacity estimation or environmental mensuration and eigenvalue decompositions of the signals over the estimated channels; (3) using channel reciprocity in a point-to-multipoint network with a set of presumed directive transmit weights pre-established for each node in said network; (4) in such a channel-reciprocity, point-to-multipoint network, pointing a signal beam in the direction of the intended recipient and guiding nulls in the directions of unintended receivers, to reduce the unintended signal to the level of the background noise; (5) in such a null-guiding network, directing maximal energy at the intended receiver and ignoring other receivers in the environment; (6) in such a null-guiding network, using directive and retrodirective beam forming between said point-to-point connections; (7) using point-to-point reciprocity for a given link; (8) using interference-whitened reciprocity between two nodes in a point-to-point network; and, (9) using SINR maximization for each particular point-to-point link (10) using a training link in a dominant mode from one node to another to establish successive SINR maximization at each end of that link; (11).
None of the above, however, have been applied to general multipoint to multipoint, or to multiple-input, multiple-output (MIMO) network which is dynamically responsive to environmental conditions, both those within and external to the network, over all the nodes and potential links amongst them. Once the nodes become capable of general multiple-output and multiple-input signal processing, some particular further approaches have been considered to increasing network capacity. These include SDMA and Multitone Transmission, as well as combinatorial coding schemes.
Spatial Separation of Signals
Spatial filtering techniques (separation of signals based on their observed spatial separation at transceivers) can be used to boost network capacity in a variety of manners. Approaches used in prior art include reuse enhancement, in which fixed (e.g., sectorized antenna arrays) or adaptive (e.g., adaptive array processing) spatial filtering is used to reduce or control interference between centralized transceivers (e.g., BS's) and edge nodes (e.g., SU's) using the frequency or time resource (e.g., time slot or frequency channel) in different cells of cellular PMP networks, thereby reducing the geographical separation between those cells and therefore the frequency reuse factor employed by the network; and space diversity multiple access (SDMA), in which a centralized transceiver uses spatial filtering to establish simultaneous links with multiple edge transceivers operating on the same frequency or time resource in PMP or cellular PMP networks.
The SDMA transmission protocol involves the formation of directed beams of energy, whose radiation patterns do not overlap with each other, to communicate with users at different locations. Adaptive antennae arrays can be driven in phased patterns to simultaneously steer energy in the direction of selected receivers. With such a transmission technique, the other multiplexing schemes can be reused in each of the separately directed beams. For example, in FDMA systems, the same frequency channel can be used to link to two spatially separated nodes, using two different spatially separated beams. Accordingly, if the beams do not overlap each other, different users can be assigned the same frequency channel as long as they can be uniquely identified by a specific beam/channel combination.
The SDMA receive protocol involves the use of multi-element adaptive antennae arrays to direct the receiving sensitivity of the array toward selected transmitting sources. Digital beamforming is used to process the signals received by the adaptive antennae array and to separate interference and noise from genuine signals received from any given direction. For a receiving station, received RF signals at each antenna element in the array are sampled and digitized. The digital baseband signals then represent the amplitudes and phases of the RF signals received at each antenna element in the array. Digital signal processing (DSP) techniques are then applied to the digital stream from each antenna element in the array. The process of beamforming involves the application of weight values to the digital signals from each antenna element (‘transmit weights’), thereby adjusting the numerical representation of their amplitudes and phases such that, when added together, they form the desired beam—i.e. the desired directional receive sensitivity. The beam thus formed is a digital representation within the computer of the physical RF signals received by the antennae array from any given direction. The process of null steering at the transmitter is used to position the spatial direction of null regions in the pattern of the transmitted RF energy. The process of null steering at the receiver is a DSP technique to control the effective direction of nulls in the receiver's gain or sensitivity. Both processes are intended to minimize inter-beam spatial interference. SDMA techniques using multi-element antennae arrays to form directed beams are disclosed in the context of mobile communications in Swales, et. al., IEEE Trans. Veh. Technol. Vol. 39 No. 1 February, 1990 and in U.S. Pat. No. 5,515,378, which also suggests combining various temporal and spectral multiple-access techniques with spatial multiple access techniques. The technical foundations for SDMA protocols using adaptive antennae arrays are discussed, for example, in the book by Litva and Lo entitled “Digital Beamforming in Wireless Communications”, Artech House, 1996. And in U.S. Pat. No. 5,260,068, Gardner and Schell suggest conjoining “spectrally disjoint” and “spatially separable” electromagnetic signal patterns.
Also, in the work by Agee cited supra, at p. 72, he notes: “[s]patial diversity can be exploited for any networking approach and modulation format, by employing a multiport adaptive antenna array to separate the time-coincident subscriber signals prior to the demodulation operation.”
In his above-referenced patents, Raleigh also mentions reuse enhancement methods that use adaptive spatial filtering to reduce reuse factor of 2G FDMA-TDMA networks. Fixed (sectorized) spatial filtering is also employed in 2G CDMA networks to increase the number of codes that can be used at BS's in the network.
When a transmitter communicates the transmit weights, the receiver can use them to compare against the received signals to eliminate erroneously received spatially separated signals (i.e., reflections of other spatial sector signals unintentionally received). The receiver can also generate a set of ‘receive weights’ which indicate that DSP formulation which best recreated, out of the universe of received signals from the multipath elements, the original signal as modified by the now-known transmit weights (as differentiated from the signal modified by the transmit path).
In U.S. Pat. No. 6,128,276, Agee disclosed that not only can multiple antennae be used in a diversity scheme from a single transmitting antenna, but also that the receiving antennae need only as much separation as is necessary “to vary different multipath interference amongst the group. A separation of nominally ten wavelengths is generally needed to observe independent signal fading.” Although, as mobile wireless is moving up-frequency the wavelengths are shortening in direct inverse order, this ten-wavelength separation still imposed a practical limit. Most wireless communications networks today are still working in the 1-to-5 GHz range, where the single wavelengths measure between a meter and a decimeter. While a decimeter separation (3.937) could fit within the average size of a handheld cellular unit, a 10-decimeter, or even a 10-meter, separation, would not. And fitting multiple decimeter antennae requires, of course, even more separation space between the antennae.
Spatial separation techniques, and in particular techniques based on fixed spatial filtering approaches, suffer from what may be called ‘dynamic’ multipath. They can be substantively harmed by channel multipath. Signal reflections may impinge on the spatially sensitive transceiver from any and all directions, including directions opposite from the transceiver (e.g., due to structures on the far side of the transceiver). These reflections can cause signals expected on one sector to be injected into other sectors, causing undesired interference. Dealing with known and presumed multipath, and depending upon it, are not the same as opportunistically using the optimal subset of potential multipaths, which is not part of these or other prior art.
Additional Diversity Available in a MIMO Environment
With multiple antennae at the transmitting and receiving end, three further diversity schemes become accessible. The first two are mentioned in U.S. Pat. No. 6,128,276, those being angle-of-arrival and polarization diversity. The third is spectral diversity, obtained by redundantly transmitting the signal data over multiple frequency channels. In this approach, both the phase and amplitude of the carrier can be varied to represent the signal in multitone transmissions and M-ary digital modulation schemes. In an M-ary modulation scheme, two or more bits are grouped together to form symbols and one of the M possible signals is transmitted during each period. Examples of M-ary digital modulation schemes include Phase Shift Keying (PSK), Frequency Shift Keying (FSK), and higher order Quadrature Amplitude Modulation (QAM). In QAM a signal is represented by the phase and amplitude of a carrier wave. In high order QAM, a multitude of points can be distinguished on an amplitude/phase plot. For example, in 64-ary QAM, 64 such points can be distinguished. Since six bits of zeros and ones can take on 64 different combinations, a six-bit sequence of data symbols can, for example, be modulated onto a carrier in 64-ary QAM by transmitting only one value set of phase and amplitude out of the possible 64 such sets.
Varanesi cavalierly dismissed MIMO, his assessment being: “While mathematically elegant and sound, the critique of that general approach is that, in practical situations, one is usually not interested in over-achieving reception fidelity. It is sufficient to just meet a performance specification. So rather than achieving that performance without overkill, the leftover is used to make the system more bandwidth efficient.” His patent also gives no consideration to either (a) network effects and how to attain them beneficially; and (b) using multi-user feedback decision receivers (or obviously, multi-user feedback) anywhere but at BSs.
Various methods for obtaining signal diversity are known. Frequency diversity is one of many diversity methods. The same modulation is carried by several carrier channels separated by nominally the coherence bandwidth of each respective channel. In time diversity, the same information is transmitted over different time slots.
Multiple antennas can be used in a spatial diversity scheme. Several receiving antennas can be used to receive the signals sent from a single transmitting antenna. For best effect, the receiving antennas are spaced enough apart to vary different multipath interference amongst the group. A separation of nominally ten wavelengths is generally needed to observe independent signal fading.
Signal diversity can be used when a signal has a bandwidth much greater than the coherence bandwidth of the channel, in a more sophisticated diversity scheme. Such a signal with a bandwidth W can resolve the multipath components and provide the receiver with several independently fading signal paths. When a bandwidth W much greater than the coherence bandwidth of each respective channel is available to a user, the channel can be subdivided into a number of frequency division multiplexed sub-channels having a mutual separation in center frequencies of at least the coherence bandwidth of each respective channel. The same signal can then be transmitted over the frequency-division multiplex sub-channels to establish frequency diversity operation. The same result can be achieved by using a wideband binary signal that covers the bandwidth W.
Other prior art diversity schemes have included angle-of-arrival or spatial diversity and polarization diversity. Many of these, and the prior art thereof, are referenced in U.S. Pat. No. 6,128,276, B. G. Agee, “Stacked-Carrier discrete multiple tone communication technology and combinations with code nulling, interference cancellation, retrodirective communication and adaptive antenna arrays”. In that patent, one of its main objectives was to provide a simple equalization of linear channel multipath distortion; yet one of its principle limitations is that it concentrates on point-to-multipoint communication links: “But this technique is extended by the present invention to point-to-point and point-to-multipoint communications where the intended communicators, as well as the interferers, include stacked-carrier spread spectrum modulation formats.” Although U.S. Pat. No. 6,128,276 mentions multipoint-to-multipoint and point-to-point alternatives, it does not provide a unified approach for network MIMO management which exploits advantageously the localization efforts of individual nodes. One key difference is that while in the present invention, any node may be a transceiver for multiple inputs and multiple outputs, in U.S. Pat. No. 6,128,276 “A difference between the base station and the remote unit is that the base station transceives signals from multiple nodes, e.g., multiple access. Each remote unit transceives only the single data stream intended for it. Channel equalization techniques and code nulling are limited methods for adapting the spreading and despreading weights.” Furthermore, unlike the present invention where the transmit and receive weights are substantially the same and preferentially form a reciprocal, in U.S. Pat. No. 6,128,276: “In general, the despreading weights are adjusted to maximize the signal-to-interference-and-noise ratio (SINR) of the despread baseband signals, e.g., estimated data symbols. This typically results in a set of code nulling despreading weights that are significantly different than the spreading gains used to spread the baseband signals at the other ends of the link.” Additionally, the preferred embodiment in U.S. Pat. No. 6,128,276 uses blind despreading as it presumes that “the transmit spreading gains and channel distortions are not known at the despreader”, whereas the present invention embodies symbol signaling to allow the spreading gains and channel distortions to be known at each end of the link.
OFDM
With multitone transmission, Orthogonal Frequency Division Multiplexing OFDM) becomes more feasible from each node equipped with a multi-antennae array. There have been several problems in dynamic wireless electromagnetic communication networks implementing OFDM (which include both those designed with static and mobile nodes, and those designed with only static nodes that must adapt over time to environmental or network changes, additions, or removals). These problems include intertone interference, windowing time constraints (generally requiring short windows), and inapplicability to macrocellular, i.e. multi-cell, network deployment. One of the objects of the present embodiment of the invention is to overcome these and other current OFDM problems in a MIMO environment.
DS-CDMA Problems
P. N. Monogioudis and J. M. Edmonds, in U.S. Pat. No. 5,550,810, identified several problems in Direct-Sequence, Code Division Multiple Access approaches to resolving multipath and multiple transmitter conditions. In a DS-CDMA communication system a digital signal, for example digitized speech or data, is multiplied by a coding sequence comprising a pseudorandom sequence which spreads the energy in the modulating signal, which energy is transmitted as a spread spectrum signal. At the receiver, the antenna signal is multiplied by the same pseudorandom sequence which is synchronized to the spreading sequence in order to recover the modulating signal. Due to multipath effects which will cause intersymbol interference, Rake combining is used to overcome these effects and to produce a modulating signal which can be demodulated satisfactory.
In the case of a DS-CDMA communication system several different spread spectrum signals having the same or different chip rams and transmitted simultaneously at the same frequency by different users may be received at an antenna, each signal having been subject to different multipath effects, a method of equalization which attempts to determine the channel impulse response and invert it is not adequate. Amongst the problems is what is known as the near-far effect due to signals from transmitters being received at a BS at different power levels. This effect is overcome by the BSs having fast power control algorithms.
In order for a receiver to be able to adapt itself to different conditions which may be found in practice, it must be able to cope with multiple bit rates which are required by a multi-media service provision, variations in the loading of the system, bit error degradation that other users' interference causes and power control failure caused, for example, by near-far interference under severe fading conditions.
They identify the information-theory source for that patent's incorporated canceller for intersymbol interference, but note that:                “A problem with DS-CDMA is that there may be several different simultaneous transmissions on the same frequency channel, which transmissions may be asynchronous and at different bit rates. Accordingly in order to approach the performance of a single user it is not sufficient just to estimate the channel impulse response and perform combining.”        
Where they do consider MIMO it is only in the context of a single BS recovering signals from several users; and because of the problems they identified above, mostly dismissed the MIMO approach, stating:                “For dealing with multi-user interference in DS-CDMA transmissions, decision feedback equalizers are not good enough because they do not obtain, and make use of, tentative decisions obtained independently from the received transmissions.”        
None of the prior art resolved a basic problem with wireless communication, that the greater the power that goes into one transmission the less capacity other transmissions may experience, for one person's signal is another person's noise. By approaching all wireless multipoint electromagnetic communications networks solely from the individual unit level, this conundrum continually represented a barrier.
Power vs. Capacity Conundrum
Ongoing power control for a wireless electromagnetic communications network is the control of radiated power, as the communication environment changes after initial communications between any two nodes is attained. The signal transmitted from one node to another becomes part of the environment, and thus part of the ‘noise’, for any other communication. Not only can such a signal interfere with other simultaneous conversations between other, unrelated pairs of nodes in the network, but it can also interfere with simultaneous conversations between other nodes and the receiving (or even sending) node. Two types of power control are necessary: initial power control (to establish a minimally acceptable communications channel or link between a transmitting and receiving node), and ongoing power control, to constantly adapt the minimum level of power usage as the environment changes.
Power Consumption as a Second, Orthogonal Network Metric
Initial Power Control
Several communications protocols are known for cellular systems. These range from the Personal Handiphone System (PHS) and the Global System for Mobile Communications (GSM), to the packet-switching TCP/IP protocol, the new ‘BlueTooth’ limited range protocol, and a host of pager-based protocols. All must manage the initialization between one node and another, a problem that has plagued communications since the day Alexander Graham Bell's proposed ‘Hoi, Hoi!’ fought with Thomas A. Edison's “Hello”.
Similarly, the amount of power which must be used to establish the initial link between any two nodes is only known to the extent that the environment (external and internal) is identical to previously established conditions. If no record of such conditions exist, either because the cost of storing the same information is too high, or because no such link has ever been made, or because an environmental difference has already been detected, then the initial power allocation which must be made is uncertain. The higher the initial power used to establish a link, the greater that link's impact will be on other links and upon the reciprocal nodes at either end. At the high extreme the new link will drown out all existing links, thereby degrading network capacity; at the low extreme, the new link will not be discernible, thereby failing to establish new capacity. Moderating the initial power over time, as links are formed, broken, and reformed, currently requires good luck, insensitivity to environmental conditions and preference for ad-hoc assertions, complex record maintenance, or increased effort at ongoing power control. An approach of using power management and reciprocal transmit weights, while it provides some adaptivity, fails to attain the capacity and power management potential of full diversity utilization.
Ongoing Power Control
Ongoing power control is the control at the transmitter as the communication environment changes after the link amongst a set of nodes is achieved. For example, when radiated power at the sender is increased for the link between a sender and recipient(s), in order to achieve an acceptable quality for the received signal, such a change may degrade other signals at the same node(s) and in ‘nearby’ links. In addition, as connections are constantly altering (nodes adding and subtracting signals as content flows and halts), the power assignments may change, again affecting the environment of radiated signals. There is a range of ‘acceptable’ signal, with the two extremes of ‘excess quality’ (implying that excess RF power is being used by the transmitter), and ‘unacceptable quality’ (implying that inadequate RF power is being used by the transmitter. Variations in propagation characteristics, atmospherics, and man-made interference (e.g., respectively, transmission hardware operational fluctuations, lightning, and noisy spark plugs in vehicles around the node) can also require the adjustment of the RF power levels.
The environmental changes that must be adapted to, and may require power changes in the transmission, may be changes external to the network. These can come from broad, general changes in the weather, particular and local changes in the immediate environment of a node (such as human or animal interaction with an antenna or the electromagnetic signal), changes in background interference, or particular and transient changes in complex environments which contain mobile elements that can affect transmissions, such as moving vehicles or airplanes passing through the signal space.
Other environmental changes that must be adapted to, and may require power changes in the transmission, may be changes internal to the network. These can include the addition (or dropping) of other unrelated signals between disparate links which affect the capacity attainable by the sending and receiving link, the addition (or dropping) of other signals between the receiving node and other nodes, or the addition (or dropping) of other signals between the sending node and other nodes.
Objective of Power Control
The objective of power control, especially of ongoing power control, is to minimize the power transmitted at each node in the network, to allow each node to achieve a desired level of performance over each link in the network, e.g., to attain a ‘target’ signal-to-interference-plus-noise (SINR) ratio for every link in the network. Such a power control method is referred to herein as a globally optimizing power control method. If a method is designed solely to optimize the SINR ratio at some subset of the network (e.g. a particular node, or a sub-set of nodes), then it is referred to herein as a locally optimizing power control method.
The problem has been that any globally optimizing power control method requires either impractical availability of hardware at each node, or unacceptably high communication of overhead control data to manage the entire network. Solutions have been proposed for a number of particular sub-sets of communications protocols, hardware, or systems, but none have resolved both the overhead vs. content and power vs. capacity conundrums both locally and globally.
A method for power control is disclosed in “Power Control With Signal Quality Estimation For Smart Antenna Array Communication Systems”, PCT International Application PCT/US/02339, which is a continuation-in-part of U.S. patent application Ser. No. 08/729,387. This application uses particularized power assignments for each link rather than a global power capacity target, and, in focusing entirely on managing the power vs. capacity conundrum, does not address the overhead vs. content conundrum.
Similarly, Farrokh Rashid-Farrokhi, Leandros Tassiulas, and K. J. Ray Liue proposed a theoretical approach to power management using link-by-link, or link-based, SINR performance metrics. (See, Farrokh Rashid-Farrokhi, Leandros Tassiulas, and K. J. Ray Liu, “Joint optimal power control and beamforming in wireless networks using antenna arrays,” IEEE Transactions on Communications, vol. 46, pp. 1313-1324, 1998; Farrokh Rashid-Farrokhi, K. J. Ray Liu, and Leandros Tassiulas, “Transmit beamforming and power control for cellular wireless systems,” IEEE Journal on Selected Areas in Communications, vol. 16, pp. 1437-1450, 1998. The prior art did not address either MIMO channels or multipoint networks, chiefly considered fixed SINR constraints rather than dynamically adaptive network constraints. And failed to address real-world QoS requirements for individual subscribers in the network. Since a user can generally be connected to the network over multiple channels, multipath modes, and even be connected to multiple nodes in the network, a more realistic requirement would be to consider the total information rate into or out of a given node. This fundamental issue can not be addressed by the prior art, but is addressed by the LEGO concept. The suite of LEGO techniques can also address other network optimization criterion that can be more appropriate for some networks. In particular the max-min capacity optimization criterion and its related offshoots permit the network to maximize its capacity performance based on current channel conditions and traffic conditions. This can be particularly important for high-speed networks, or networks that are required to provide high rate CBR services, since these networks can easily consume all the available capacity that the network can provide, subject to the transmitter power constraints. The prior art, on the other hand, requires fixed, link by link performance goals in their optimization criteria.
Because capacity and power interact with each other within a wireless communications network, any approach to network optimization must address the system-wide and dynamic interplay between these two, orthogonal, metrics. Optimization that focuses solely on the environment for each particular node in the network, just as much as optimization that focuses solely on the global internodal environment, creates the risk of unbalanced and less-than-optimal results, and weakens the dynamic stability of the network in changing environments.
Distributed Networks and Dynamic Channel Structures
Distributed networks, where any particular node may both receive and transmit data from any other node, pose many advantages over the PMP and cellular PMP networks designed around centralizing hubs. The Internet is one of the principal examples of a new distributed network, though a broad range of other application areas for such are opening out. There is an explosive demand for broadband, mobile, and portable data services via both wired and wireless networks to connect conventional untethered platforms (handsets, laptops, PDAs) with other untethered, or transient or transitory, platforms (cell phones, inventory or shipping tags, temporary service connections). In all of these applications, distributed networks can provide strong advantages over conventional systems, by exploiting the inherent advantages of connectionless data service, or by reducing the power required to communicate amongst untethered platforms, at data rates competitive with tethered devices.
Distributed networks also provide multiple advantages in military applications, including collection, analysis, and collation/dissemination of reconnaissance data from beyond the front line of troops (FLOT); intruder detection and location behind the FLOT and rear echelons. By allowing data transfer through nearby nodes and over ‘flat’ network topologies, particularly dynamic networks where the channels change according to the context and presence or absence of particular nodes, distributed networks can reduce an adversary's ability to identify, target, incapacitate, or even detect high priority nodes in the network greatly enhancing the security and survivability relative to conventional point-to-multipoint networks.
Analogous advantages accrue to security applications or to logistical management systems, where opposition may be either criminal activity or natural disasters (blizzards, floods, warehouse or other fires). One key element of any multipoint to multipoint approach is that channels of communication between any particular pair of nodes may change over time in response to the environment, said environment including both the external natural environment and the internal environment of the same network's continually shifting functions and data streams.
Moreover, this invention is concerned with the problems described below.